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Acoustic emission (AE) evaluation is an important Nondestructive Testing technique. The technique is a whole field passive technique that detects defects that are growing during the application of force on the structure. At a certain threshold, AE starts emanating from the structure while the structure is stressed by tensile deformation. 18% Ni Maraging steel 250 grade material is widely used in the aerospace industry and exhibits fracture behaviour. In the current study, tensile specimens are used and acoustic emission (AE) parameters are recorded. Four types of specimens Type A, Type B, Type C and Type D specimens are designated as heat -affected zone, parent metal, defect-free weldment and weld with notch defect, respectively. These specimens are tensile deformed in order to obtain AE parameters at 60% of failure load (FL), 60–75% of FL, 75–90% of FL and 90% to FL. AE parameters – amplitude, ring down counts, duration, rise time, energy, RA value, DA value, hit rate, count rate and energy rate – are tabulated for various FLs. These parameters have vital importance in critical assessment of the structural integrity of 18% Ni Maraging steel 250 structures. [ABSTRACT FROM AUTHOR]

Shape memory polymer composite (SMPC) exhibits the remarkable mechanical properties as compared to its corresponding shape memory polymer (SMP) without compromising the shape memory behavior. The enhancement of the mechanical and thermomechanical properties of the carbon fiber-reinforced SMPC is presented in the present study with the incorporation of graphene nanoplatelets (GnP) in the SMP matrix. The fabrication process involved the preparation of the GnP/epoxy nanocomposites through ultrasonication and shear mixing and the subsequent molding of the carbon fiber-reinforced hybrid polymer composites by hand layup technique. The mechanical and thermomechanical characterizations were conducted as per the ASTM standards, which were followed with corresponding morphological study to the explore the microscale behavior of the hybrid composites. Shape memory behavior were studied in terms of the shape recovery ( R r ) and shape fixity ( R f ) through the heat activation bending tests. The tensile strength of the hybrid composites with 0.4 and 0.6 wt% GnP content increased by 14.3% and 32.2%, respectively, as compared to unmodified SMPC. Similar trends were also indicated in the dynamic mechanical analysis (DMA) with the corresponding rise in the storage modulus and glass transition temperature due to incorporation of nanofillers. The improvement of the interfacial bonding between the fiber and matrix and wettability of carbon fiber supported these improvements. Negligible adverse effect was noticed in the shape memory behavior of the hybrid composites with the incorporation of GnP, which displayed the R r and R f of ~97% and 96%, respectively. [ABSTRACT FROM AUTHOR]

The objective of this research work was to understand the warp and weft directional tensile properties of the two-dimensional multistitched multilayer E-glass/polyester woven composites. The warp and weft directional specific tensile strength and modulus of unstitched structure were higher than those of multistitched structures as stitching caused minor warp and weft yarn filament breakages. Contrarily, the specific tensile strains of unstitched structure were slightly lower than those of all multistitched structures. The stitching yarn type, the number of stitching directions, and the stitching density generally influenced the warp and weft directional tensile properties of multistitched E-glass/polyester woven composites. The failure of warp and weft directional multistitched woven E-glass/polyester composite structures was matrix breakages, and partial and complete yarn breakages in their surfaces. They had a local delamination in their cross-sections and the delamination did not propagate to the large areas due to multidirectional stitching. Also, the failure was confined at a narrow area and resulted in the catastrophic fiber breakages. The warp and weft directional specific damaged areas of multistitched structures, in particular four-directional stitching, were significantly lower than those of the unstitched structures. This indicated that the multistitching made the structures better damage-tolerance materials. [ABSTRACT FROM AUTHOR]

Due to the characteristic that shape memory materials can quickly return to their original shape and have large deformation, such materials can be used as the connection in active disassembly devices. However, existing active disassembly devices typically require two moulding steps and complicated machining processes that result in high manufacturing cost. The active disassembly device based on the proposed decapitated head method has only one moulding step and lower manufacturing cost. Its disassembly mode is local damage disassembly, which can decrease the active disassembly cost and improve disassembly efficiency. This paper describes the active disassembly theory and the design methodology based on the decapitated head method, and then analyses the design criteria and feasibility of this method with a real case study. [ABSTRACT FROM PUBLISHER]

Sand production prediction has always been an important issue when dealing with production phenomena. Knowing all significant consequences of precise sand production prediction, different methods were developed using a variety of criteria and material models were implemented to obtain more accurate results. Although sand rate prediction has become a prevalent challenge nowadays, it does not reduce sanding onset prediction. Dealing with different methods and knowing the disadvantages of each one will clarify the necessity of developing a technique having the exactness and accuracy of numerical and experimental methods and simplicity of analytical ones. There was an endeavor in this article to apply powerful tools of an artificial neural network to predict critical bottomhole flowing pressure inhibiting sand production. Comprehensive well data gathered from 38 wells distributed in three oilfields producing from the same source rock were investigated to find the main parameters causing sand production. After verifying the proposed model with test wells, it was evaluated against well-accepted analytical models. The final results illustrate a reliable and more exact method that can predict sand initiation with a high degree of accuracy. [ABSTRACT FROM AUTHOR]